filter_correlated_cell_scExp: Filter lowly correlated cells

In vallotlab/ChromSCape: Analysis of single-cell epigenomics datasets with a Shiny App

Filter lowly correlated cells

Description

Remove cells that have a correlation score lower than what would be expected by chance with other cells.

Usage

filter_correlated_cell_scExp(scExp, random_iter = 5,
corr_threshold = 99, percent_correlation = 1,
downsample = 2500, verbose = TRUE, n_process = 250,
BPPARAM = BiocParallel::bpparam())

Arguments

scExp	A SingleCellExperiment object containing 'Cor', a correlation matrix, in reducedDims.
random_iter	Number of random matrices to create to calculate random correlation scores. (50)
corr_threshold	Quantile of random correlation score above which a cell is considered to be 'correlated' with another cell. (99)
percent_correlation	Percentage of the cells that any cell must be 'correlated' to in order to not be filtered. (1)
downsample	Number of cells to calculate correlation filtering threshold ? (2500)
verbose	Print messages ? (TRUE)
n_process	Number of cell to proceed at a time. Increase this number to increase speed at memory cost
BPPARAM	BPPARAM object for multiprocessing. See bpparam for more informations. Will take the default BPPARAM set in your R session.

Details

This functions takes as input a SingleCellExperiment object that must have correlation matrix calculated and outputs a SingleCellExperiment object without lowly correlated cells. TSNE is recalculated.

Value

Returns a SingleCellExperiment object without lowly correlated cells. The calculated correlation score limit threshold is saved in metadata.

Examples

data("scExp")
dim(scExp)
scExp_cf = filter_correlated_cell_scExp(scExp,
corr_threshold = 99, percent_correlation = 1)
dim(scExp_cf)

vallotlab/ChromSCape documentation built on Oct. 15, 2023, 1:47 p.m.